Related Experiment Video
Updated: Mar 15, 2026

07:41
Modeling the Size Spectrum for Macroinvertebrates and Fishes in Stream Ecosystems
Published on: July 30, 2019
8.1K
How Many Fish Need to Be Measured to Effectively Evaluate Trawl Selectivity?
Bent Herrmann1,2, Manu Sistiaga3, Juan Santos4
1SINTEF Fisheries and Aquaculture, Fishing Gear Technology, Willemoesvej 2, 9850, Hirtshals, Denmark.
Plos One
|August 26, 2016
Summary
Understanding fish sampling effort is crucial for trawl selectivity studies. Measuring more fish reduces uncertainty in selection parameters, with covered codends requiring less effort than paired gears.
Area of Science:
- Fisheries Science
- Marine Biology
- Quantitative Ecology
Background:
- Trawl selectivity assessments require accurate fish sampling data.
- Uncertainty in selectivity parameters can impact fisheries management.
- Standardized guidelines for sampling effort are needed by practitioners.
Purpose of the Study:
- To provide guidelines on necessary fish sampling effort for trawl selectivity sea trials.
- To determine the number of fish measurements needed to achieve specific uncertainty levels for selectivity parameters.
- To investigate how experimental methods and catch size structure influence uncertainty.
Main Methods:
- Simulated data from Barents Sea cod and Mediterranean red mullet fisheries were used.
- Analysis focused on the relationship between fish sample size and uncertainty in selection parameters.
- Comparison of sampling effort between covered codend and paired-gear methods.
Main Results:
- Uncertainty in selection parameters decreases with an increasing number of measured fish, following a power model.
- The covered codend method requires significantly less sampling effort than the paired-gear method.
- In some cases, the paired-gear method requires up to 10 times more measured fish for the same uncertainty level.
Conclusions:
- Guidelines for fish sampling effort in trawl selectivity studies can be generalized across fisheries.
- The covered codend method is more efficient in reducing uncertainty for a given sampling effort.
- Practitioners can use these findings to optimize sea trial designs and data collection strategies.

